[GRASS-user] EPSG 32633 and spatial resolution for hourly LST product from Copernicus

Nikos Alexandris nik at nikosalexandris.net
Tue Sep 25 07:51:16 PDT 2018


* Veronica Andreo <veroandreo at gmail.com> [2018-09-25 08:24:44 -0300]:

>AFAIU, plate carree (lat long grid, no meters) is deprecated, and you
>should use latlong instead. I had a similar issue with modis ocean color
>products.
>
>Do you at least get the same number of row and columns that is described by
>gdalinfo when you import?

No, it is 512^2 (see below) against
```
g.regio -p
..
rows:       3584
cols:       8064
..
```

Markus' hint, not *directly* on the netCDF file, rather on one of the
layers:

gdalinfo NETCDF:"g2_BIOPAR_LST_201606220100_GLOBE_GEO_V1.2.nc":LST
Driver: netCDF/Network Common Data Format
Files: g2_BIOPAR_LST_201606220100_GLOBE_GEO_V1.2.nc
Size is 8064, 3584
Coordinate System is:
GEOGCS["unknown",
    DATUM["unknown",
        SPHEROID["Spheroid",6378137,298.2572326660156]],
    PRIMEM["Greenwich",0],
    UNIT["degree",0.0174532925199433,
        AUTHORITY["EPSG","9122"]]]
Origin = (-180.022321429103613,80.022321429103613)
Pixel Size = (0.044642858207226,-0.044642858207226)
Metadata:
  crs#grid_mapping_name=latitude_longitude
  crs#inverse_flattening=298.2572326660156
  crs#longitude_of_prime_meridian=0
  crs#semi_major_axis=6378137
  lat#axis=Y
  lat#long_name=latitude
  lat#standard_name=latitude
  lat#units=degrees_north
  lon#axis=X
  lon#long_name=longitude
  lon#standard_name=longitude
  lon#units=degrees_east
  LST#add_offset=273.15
  LST#ancillary_variables=Q_FLAGS, ERRORBAR_LST, TIME_DELTA, PERCENT_PROC_PIXELS
  LST#cell_methods=area:mean where land
  LST#coverage_content_type=physicalMeasurement
  LST#grid_mapping=crs
  LST#long_name=Land Surface Temperature
  LST#scale_factor=0.01
  LST#standard_name=surface_temperature
  LST#units=Kelvin
  LST#valid_range={-7000,8000}
  LST#_FillValue=-8000
  NC_GLOBAL#algorithm_version=GOES13-LST_v3.40, MSG3-LST_v7.14.0, HIMAWARI8-LST_v3.50, DataFusion_v5.2
  NC_GLOBAL#archive_facility=IPMA
  NC_GLOBAL#comment=Land Surface Temperature (LST) is the radiative skin temperature over land. LST plays an important role in the physics of land surface as it is involved in the processes of energy and water exc
hange with the atmosphere. LST is useful for the scientific community, namely for those dealing with meteorological and climate models. Accurate values of LST are also of special interest in a wide range of areas
related to land surface processes, including meteorology, hydrology, agrometeorology, climatology and environmental studies.
  NC_GLOBAL#contacts=Principal investigator (Researcher): isabel.trigo at ipma.pt; Instituto Português do Mar e da Atmosfera (IPMA); Rua C ao Aeroporto; Lisbon; 1749-077; Portugal (PT); IPMA website; http://www.ipma.
pt
Originator (IPMA GIO-Global Land Help Desk): sandra.coelho at ipma.pt; Instituto Português do Mar e da Atmosfera (IPMA); Rua C ao Aeroporto; Lisbon; 1749-077; Portugal (PT); IPMA website; http://www.ipma.pt
Point of contact (GIO-Global Land Help Desk): helpdesk at vgt.vito.be; Flemish Institute for Technological Research (VITO); Boeretang 200; Mol; 2400; Belgium (BE); VITO website; http://land.copernicus.eu/global/
Owner: ENTR-COPERNICUS-ASSETS at ec.europa.eu; European Commission Directorate-General for Enterprise and Industry (EC-DGEI); Avenue d'Auderghem 45; Brussels; 1049; Belgium (BE); EC-DGEI website; http://ec.europa.eu/
enterprise/
Custodian (Responsible): copernicuslandproducts at jrc.ec.europa.eu; European Commission Directorate-General Joint Research Center (JRC); Via E.Fermi, 249; Ispra; 21027; Italy (IT); JRC website; http://ies.jrc.ec.eur
opa.eu
  NC_GLOBAL#Conventions=CF-1.6
  NC_GLOBAL#credit=LST products are generated by the land service of Copernicus, the Earth Observation programme of the European Commission. The LST algorithm, originally developed in the framework of the FP7/Geoland2, is generated from MTSAT/HIMAWARI and GOES data, respectively owned by JMA and NOAA, and combined with the LST product from MSG under copyright EUMETSAT, produced by LSA-SAF.
  NC_GLOBAL#date_created=2016-06-22T03:22:01Z
  NC_GLOBAL#gcmd_keywords=SURFACE TEMPERATURE
  NC_GLOBAL#gemet_keywords=solar radiation
  NC_GLOBAL#history=2016-06-22T03:22:01Z - Product generation;
  NC_GLOBAL#identifier=urn:cgls:global:lst_v1_0.045degree:LST_201606220100_GLOBE_GEO_V1.2
  NC_GLOBAL#inspire_theme=Orthoimagery
  NC_GLOBAL#institution=IPMA
  NC_GLOBAL#iso19115_topic_categories=climatologyMeteorologyAtmosphere, imageryBaseMapsEarthCover
  NC_GLOBAL#long_name=Land Surface Temperature
  NC_GLOBAL#name=LST
  NC_GLOBAL#orbit_type=GEO
  NC_GLOBAL#other_keywords=Global
  NC_GLOBAL#parent_identifier=urn:cgls:global:lst_v1_0.045degree
  NC_GLOBAL#platform=GOES13, MSG3, HIMAWARI8
  NC_GLOBAL#processing_level=L4
  NC_GLOBAL#processing_mode=Near Real Time
  NC_GLOBAL#product_version=V1.2
  NC_GLOBAL#purpose=This product is first designed to fit the requirements of the Global Land component of Land Service of GMES-Copernicus. It can be also useful for all applications related to the environment monitoring.
  NC_GLOBAL#references=Product User Manual: http://land.copernicus.eu/global/sites/default/files/products/GIOGL1_PUM_LST_I1.10.pdf
Validation Report: http://land.copernicus.eu/global/sites/default/files/products/GIOGL1_VR_LST_I2.10.pdf
Product page: http://land.copernicus.eu/global/products/lst
  NC_GLOBAL#sensor=IMAG, SEVI, AHI
  NC_GLOBAL#source=Data was derived from satellite imagery.
  NC_GLOBAL#time_coverage_end=2016-06-22T01:30:00Z
  NC_GLOBAL#time_coverage_start=2016-06-22T00:30:00Z
  NC_GLOBAL#title=Global Land Surface Temperature for 2016-06-22T01:00:00Z
  NETCDF_DIM_EXTRA={time}
  NETCDF_DIM_time_DEF={1,6}
  NETCDF_DIM_time_VALUES=0
  time#axis=T
  time#long_name=time
  time#units=days since 2016-06-22 01:00:00
Corner Coordinates:
Upper Left  (-180.0223214,  80.0223214) (180d 1'20.36"W, 80d 1'20.36"N)
Lower Left  (-180.0223214, -79.9776824) (180d 1'20.36"W, 79d58'39.66"S)
Upper Right ( 179.9776872,  80.0223214) (179d58'39.67"E, 80d 1'20.36"N)
Lower Right ( 179.9776872, -79.9776824) (179d58'39.67"E, 79d58'39.66"S)
Center      (  -0.0223171,   0.0223195) (  0d 1'20.34"W,  0d 1'20.35"N)
Band 1 Block=200x200 Type=Int16, ColorInterp=Undefined
  NoData Value=-8000
  Unit Type: Kelvin
  Offset: 273.15,   Scale:0.01
  Metadata:
    add_offset=273.15
    ancillary_variables=Q_FLAGS, ERRORBAR_LST, TIME_DELTA, PERCENT_PROC_PIXELS
    cell_methods=area:mean where land
    coverage_content_type=physicalMeasurement
    grid_mapping=crs
    long_name=Land Surface Temperature
    NETCDF_DIM_time=0
    NETCDF_VARNAME=LST
    scale_factor=0.01
    standard_name=surface_temperature
    units=Kelvin
    valid_range={-7000,8000}
    _FillValue=-8000


So, the important bits are:

```
gdalinfo NETCDF:"g2_BIOPAR_LST_201606220100_GLOBE_GEO_V1.2.nc":LST |grep Pixel

Pixel Size = (0.044642858207226,-0.044642858207226)
```
and
```
gdalinfo NETCDF:"g2_BIOPAR_LST_201606220100_GLOBE_GEO_V1.2.nc":LST |grep Coordinates -A5

Corner Coordinates:
Upper Left  (-180.0223214,  80.0223214) (180d 1'20.36"W, 80d 1'20.36"N)
Lower Left  (-180.0223214, -79.9776824) (180d 1'20.36"W, 79d58'39.66"S)
Upper Right ( 179.9776872,  80.0223214) (179d58'39.67"E, 80d 1'20.36"N)
Lower Right ( 179.9776872, -79.9776824) (179d58'39.67"E, 79d58'39.66"S)
Center      (  -0.0223171,   0.0223195) (  0d 1'20.34"W,  0d 1'20.35"N)
```

A fresh Location:
```
grass -c 'epsg:4326' /geo/grassdb/lst/wgs84
```
and
```
g.region -p

projection: 3 (Latitude-Longitude)
zone:       0
datum:      wgs84
ellipsoid:  wgs84
north:      1N
south:      0
west:       0
east:       1E
nsres:      1
ewres:      1
rows:       1
cols:       1
cells:      1
```

Import using r.in.gdal, _without_ any of `-l` or `-a` and then I get the
closest to the reported spatial resolution. Else, with `-a`, for
example, the spatial resolution is not as close to the "original" one.
Makes sense?

```
r.in.gdal in=NETCDF:"g2_BIOPAR_LST_201606220300_GLOBE_GEO_V1.2.nc":LST output=g2_BIOPAR_LST_201606220300_GLOBE_GEO_V1.2.nc_LST -o

WARNING: Datum <unknown> not recognised by GRASS and no parameters found
Over-riding projection check
360 degree EW extent is exceeded by 0.000192261 cells
Importing raster map <g2_BIOPAR_LST_201606220300_GLOBE_GEO_V1.2.nc_LST>...
 100%
```

Here,
```
r.info g2_BIOPAR_LST_201606220300_GLOBE_GEO_V1.2.nc_LST -g

360 degree EW extent is exceeded by 0.00019226 cells
north=80.0223214291667
south=-79.9776823855556
east=179.977687153889
west=-180.022321429167
nsres=0.0446428582072328
ewres=0.0446428582072241
rows=3584
cols=8064
cells=28901376
datatype=CELL
ncats=0
```

Then, setting the region:
```
g.region raster=g2_BIOPAR_LST_201606220300_GLOBE_GEO_V1.2.nc_LST -pg
360 degree EW extent is exceeded by 0.00019226 cells
360 degree EW extent is exceeded by 0.00019226 cells
360 degree EW extent is exceeded by 0.00019226 cells
360 degree EW extent is exceeded by 0.00019226 cells
projection=3
zone=0
n=80.0223214291667
s=-79.9776823855556
w=-180.022321429167
e=179.977687153889
nsres=0.0446428582072328
ewres=0.0446428582072241
rows=3584
cols=8064
cells=28901376
```

Better to cut off the west side (?):
```
g.region raster=g2_BIOPAR_LST_201606220100_GLOBE_GEO_V1.2.nc_LST -pag w=-180 e=180

360 degree EW extent is exceeded by 0.00019226 cells
360 degree EW extent is exceeded by 0.00019226 cells
360 degree EW extent is exceeded by 0.00019226 cells
projection=3
zone=0
n=80.0223214291667
s=-79.9776823855556
w=-180
e=180
nsres=0.0446428582072328
ewres=0.0446428571428571
rows=3584
cols=8064
cells=28901376
```

How does this look like?  We had this questions not along ago.

Nikos
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